• Corpus ID: 8543353

The Retinex Theory of Color Vision SCIENTIFIC AMERICAN

  title={The Retinex Theory of Color Vision SCIENTIFIC AMERICAN},
  author={Edwin Herbert Land},
  • E. Land
  • Published 2009
  • Computer Science
The review of color balance method for UAV image By COMPUTER technology
This paper reviews and compares the classic color balance methods of brightness equalization currently and gives a detailed explanation and effect of the application of each method.
Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation
The green stability assumption is proposed that can be used to fine-tune the values of some common illumination estimation methods by using only non-calibrated images, and the obtained accuracy is practically the same as when training on calibrated images, but the whole process is much faster since calibration is not required and thus time is saved.
Unsupervised Learning for Color Constancy
An unsupervised learning-based method is proposed that learns its parameter values after approximating the unknown ground-truth illumination of the training images, thus avoiding calibration and outperforms all statistics-based and many learning- based methods in terms of accuracy.
Deep Learning-Enabled Low-light Image Enhancement In Maritime Video Surveillance
The experimental results show that the depth network proposed in this paper improves the brightness and contrast with the monitoring images of the inland river bridge area and further improves the monitoring effect ofThe inland river bridges area, thus providing a guarantee of water traffic safety in the bridge area to a certain extent.
Degrade is Upgrade: Learning Degradation for Low-light Image Enhancement
A novel two-step generation network for degradation learning and content refinement that is not only superior to one-step methods, but also is capable of synthesizing sufficient paired samples to benefit the model training.
Feature Fusion Network for Low-Light Image Enhancement
  • Yabin Yu
  • Computer Science
    Journal of Physics: Conference Series
  • 2021
A method is proposed in this paper to tackle low-light image enhancement that fuses the high level and the low level feature, uses an attention module to model the context information and selects the critical feature to supplemented the highlevel feature to reconstruct the enhanced image.
Lane Line Extraction in Raining Weather Images by Ridge Edge Detection with Improved MSR and Hessian Matrix
By testing hundreds of images of the lane lines at raining weather and by comparing several traditional image enhancement and segmentation algorithms, the new method of thelane line detection can produce the satisfactory results.
Legibility Enhancement of Papyri Using Color Processing and Visual Illusions: A Case Study in Critical Vision
Using synergetically a range of enhancement methods and interaction modalities is suggested for optimal results and user satisfaction, and the methods that most successfully enhanced script legibility were those that leverage human perception.
Semantically Contrastive Learning for Low-light Image Enhancement
This paper proposes an effective semantically contrastive learning paradigm for LLE (namely SCL-LLE), which surpasses the state-of-thearts LLE models over six independent cross-scenes datasets and its potential to benefit the downstream semantic segmentation under extremely dark conditions is discussed.
A flying grey ball multi-illuminant image dataset for colour research
The proposed method involves using a drone to carry a grey ball of known percent surface spectral reflectance throughout a scene while photographing it frequently during the flight using a calibrated camera, which provides a measure of the illumination colour at that location.